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ORCIDRobin Chan 0001
Person information
- affiliation: Technical University of Berlin, Germany
- affiliation (2022 - 2024): Bielefeld University, Germany
- affiliation (PhD 2022): University of Wuppertal, Germany
Other persons with the same name
- Robin Shing Moon Chan
![[0009-0007-1319-8334]](https://google.otrosproyectosundfe.com/https://dblp.org/img/orcid-mark.12x12.png "0009-0007-1319-8334")
(aka: Robin Chan 0002) — ETH Zurich, Switzerland
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2020 – today
- 2025
[c11]Riza Velioglu, Petra Bevandic, Robin Chan, Barbara Hammer:
MGT: Extending Virtual Try-Off to Multi-Garment Scenarios. ICCVW 2025: 6098-6107- [i16]Riza Velioglu, Petra Bevandic, Robin Chan, Barbara Hammer:
Enhancing Person-to-Person Virtual Try-On with Multi-Garment Virtual Try-Off. CoRR abs/2504.13078 (2025) - 2024
- [c10]Riza Velioglu, Robin Chan, Barbara Hammer:
FashionFail: Addressing Failure Cases in Fashion Object Detection and Segmentation. IJCNN 2024: 1-8 - [c9]Youssef Shoeb, Robin Chan, Gesina Schwalbe, Azarm Nowzad, Fatma Güney, Hanno Gottschalk:
Have We Ever Encountered This Before? Retrieving Out-of-Distribution Road Obstacles from Driving Scenes. WACV 2024: 7381-7391 - [i15]Riza Velioglu, Robin Chan, Barbara Hammer:
FashionFail: Addressing Failure Cases in Fashion Object Detection and Segmentation. CoRR abs/2404.08582 (2024) - [i14]Dennis Rochau, Robin Chan, Hanno Gottschalk:
New advances in universal approximation with neural networks of minimal width. CoRR abs/2411.08735 (2024) - [i13]Riza Velioglu, Petra Bevandic, Robin Chan, Barbara Hammer:
TryOffDiff: Virtual-Try-Off via High-Fidelity Garment Reconstruction using Diffusion Models. CoRR abs/2411.18350 (2024) - 2023
- [j1]Robin Chan, Radin Dardashti, Meike Osinski, Matthias Rottmann, Dominik Brüggemann, Cilia Rücker, Peter Schlicht, Fabian Hüger, Nikol Rummel, Hanno Gottschalk:
What should AI see? Using the public's opinion to determine the perception of an AI. AI Ethics 3(4): 1381-1405 (2023) - [c8]Robin Chan, Sarina Penquitt, Hanno Gottschalk:
LU-Net: Invertible Neural Networks Based on Matrix Factorization. IJCNN 2023: 1-10 - [i12]Robin Chan, Sarina Penquitt, Hanno Gottschalk:
LU-Net: Invertible Neural Networks Based on Matrix Factorization. CoRR abs/2302.10524 (2023) - [i11]Youssef Shoeb, Robin Chan, Gesina Schwalbe, Azarm Nowzad, Fatma Güney, Hanno Gottschalk:
Have We Ever Encountered This Before? Retrieving Out-of-Distribution Road Obstacles from Driving Scenes. CoRR abs/2309.04302 (2023) - 2022
- [b1]Robin Chan:
Detecting Anything Overlooked in Semantic Segmentation. University of Wuppertal, Germany, 2022 - [c7]Kira Maag, Robin Chan, Svenja Uhlemeyer, Kamil Kowol, Hanno Gottschalk:
Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects. ACCV (5) 2022: 476-494 - [i10]Robin Chan, Svenja Uhlemeyer, Matthias Rottmann, Hanno Gottschalk:
Detecting and Learning the Unknown in Semantic Segmentation. CoRR abs/2202.08700 (2022) - [i9]Julian Burghoff, Robin Chan, Hanno Gottschalk, Annika Mütze, Tobias Riedlinger, Matthias Rottmann, Marius Schubert:
Uncertainty Quantification and Resource-Demanding Computer Vision Applications of Deep Learning. CoRR abs/2205.14917 (2022) - [i8]Robin Chan, Radin Dardashti, Meike Osinski, Matthias Rottmann, Dominik Brüggemann, Cilia Rücker, Peter Schlicht, Fabian Hüger, Nikol Rummel, Hanno Gottschalk:
What should AI see? Using the Public's Opinion to Determine the Perception of an AI. CoRR abs/2206.04776 (2022) - [i7]Kira Maag, Robin Chan, Svenja Uhlemeyer, Kamil Kowol, Hanno Gottschalk:
Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects. CoRR abs/2210.02074 (2022) - 2021
- [c6]Robin Chan, Matthias Rottmann, Hanno Gottschalk:
Entropy Maximization and Meta Classification for Out-of-Distribution Detection in Semantic Segmentation. ICCV 2021: 5108-5117 - [c5]Robin Chan, Krzysztof Lis, Svenja Uhlemeyer, Hermann Blum, Sina Honari, Roland Siegwart, Pascal Fua, Mathieu Salzmann, Matthias Rottmann:
SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation. NeurIPS Datasets and Benchmarks 2021 - [i6]Robin Chan, Krzysztof Lis, Svenja Uhlemeyer, Hermann Blum, Sina Honari, Roland Siegwart, Mathieu Salzmann, Pascal Fua, Matthias Rottmann:
SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation. CoRR abs/2104.14812 (2021) - 2020
- [c4]Matthias Rottmann, Kira Maag, Robin Chan, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
Detection of False Positive and False Negative Samples in Semantic Segmentation. DATE 2020: 1351-1356 - [c3]Robin Chan, Matthias Rottmann, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
Controlled False Negative Reduction of Minority Classes in Semantic Segmentation. IJCNN 2020: 1-8 - [c2]Matthias Rottmann, Pascal Colling, Thomas-Paul Hack, Robin Chan, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities. IJCNN 2020: 1-9 - [i5]Robin Chan, Matthias Rottmann, Hanno Gottschalk:
Entropy Maximization and Meta Classification for Out-Of-Distribution Detection in Semantic Segmentation. CoRR abs/2012.06575 (2020)
2010 – 2019
- 2019
- [c1]Robin Chan, Matthias Rottmann, Radin Dardashti, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
The Ethical Dilemma When (Not) Setting up Cost-Based Decision Rules in Semantic Segmentation. CVPR Workshops 2019: 1395-1403 - [i4]Robin Chan, Matthias Rottmann, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
Application of Decision Rules for Handling Class Imbalance in Semantic Segmentation. CoRR abs/1901.08394 (2019) - [i3]Robin Chan, Matthias Rottmann, Radin Dardashti, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
The Ethical Dilemma when (not) Setting up Cost-based Decision Rules in Semantic Segmentation. CoRR abs/1907.01342 (2019) - [i2]Matthias Rottmann, Kira Maag, Robin Chan, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
Detection of False Positive and False Negative Samples in Semantic Segmentation. CoRR abs/1912.03673 (2019) - [i1]Robin Chan, Matthias Rottmann, Fabian Hüger, Peter Schlicht, Hanno Gottschalk:
MetaFusion: Controlled False-Negative Reduction of Minority Classes in Semantic Segmentation. CoRR abs/1912.07420 (2019)
Coauthor Index
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